UIGen: a hybrid framework for underwater image encryption based on evolutionary chaotic system and multi-domain...

Area of Science:

• Marine research and underwater imaging
• Cybersecurity and data protection
• Signal processing and image encryption

Background:

• Underwater images are vital for marine research, surveillance, and communication.
• Aquatic environments present unique challenges like light scattering, turbidity, and limited bandwidth, degrading image quality and security.
• Existing encryption methods struggle to maintain both high security and image fidelity in submerged conditions.

Purpose of the Study:

• To develop a novel and secure encryption method, UIGen, specifically for underwater images.
• To address the inherent security challenges and vulnerabilities in the aquatic environment.
• To ensure the confidentiality, integrity, and high fidelity of underwater images.

Main Methods:

• Utilizing Non-Subsampled Shearlet Transform (NSST) for multi-scale feature extraction.
• Implementing a dynamic key generation approach based on hyper-chaotic parameters for enhanced security.
• Applying a Genetic Algorithm (GA) for optimizing encryption parameters and system robustness.

Main Results:

• UIGen effectively extracts multi-scale features, representing both coarse and fine image details.
• The hyper-chaotic key generation enhances sensitivity and overall encryption security.
• The Genetic Algorithm optimizes parameters, improving system robustness and adaptability.
• Experimental results show UIGen maintains structural integrity and high entropy.
• The method demonstrates resistance to underwater-specific attacks.

Conclusions:

• UIGen provides a robust and secure solution for underwater image encryption.
• The method successfully balances high security with image fidelity under challenging aquatic conditions.
• UIGen is adaptable to varying underwater environments, ensuring reliable data protection.